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1.
J Dairy Sci ; 102(5): 4522-4535, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30852004

RESUMO

Automatic milking systems (AMS) are installed on a growing number of dairy farms worldwide. Management to support good udder health might be different on farms with an AMS compared with farms milking with a conventional milking system, as risk factors for mastitis on farms using an AMS may differ. The aim of this study was to identify farm level factors associated with mastitis on Dutch dairy farms using an AMS. In 2008, risk factor data were collected using a questionnaire combined with on-farm recordings of cow, stall, and AMS hygiene on 135 farms. These risk factor data were linked to 4 udder-health-associated dependent variables: average herd somatic cell count (HeSCCav), variance of the average herd somatic cell count (SCC) on test days (HeSCCvar), the average proportion of new high SCC cases (NHiSCC), and the farmer-reported annual incidence rate of clinical mastitis (IRCM). We employed regression models using multiple imputation to deal with missing values. Due to the high dimensionality of the risk factor data, we also performed nonlinear principal component analysis (NLPCA) and regressed the dependent variables on the principal components (PC). Good hygiene of cows and of AMS were found to be related to a lower HeSCCav and less NHiSCC. Effective postmilking teat disinfection was associated with a lower NHiSCC. A higher bulk tank milk SCC threshold for farmers' action was related to more NHiSCC. Larger farm size was related to lower HeSCCvar but higher NHiSCC. Negative attitude of farmers to animal health, higher frequency of checking AMS, and more time spent on viewing computer data were all positively related to higher IRCM. An NLPCA with 3 PC explained 16.3% of the variance in the risk factor variables. Only the first 2 PC were associated with mastitis. The first PC reflected older and larger farms with poor cow hygiene and AMS hygiene, and was related to higher HeSCCav and NHiSCC, whereas the second PC reflected newly built smaller farms with poor cow hygiene and low milk production, and was associated with higher HeSCCvar and NHiSCC, but lower IRCM. Our study suggests that many of the risk factors on conventional milking system farms are applicable to AMS farms, specifically concerning hygiene of the cows and the milking machine, but on large AMS farms, udder health may need more attention than on smaller AMS farms. Multiple imputation is instrumental to deal with missing values and NLPCA is a useful technique to process high dimensional data in our study.


Assuntos
Indústria de Laticínios/métodos , Fazendas , Animais , Bovinos , Feminino , Mastite Bovina/imunologia , Países Baixos , Análise de Componente Principal , Análise de Regressão , Fatores de Risco
2.
Bone Marrow Transplant ; 46(3): 443-7, 2011 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-20531283

RESUMO

The European Clinical Trials Directive (EU 2001; 2001/20/EC) was introduced to improve the efficiency of commercial and academic clinical trials. Concerns have been raised by interested organizations and institutions regarding the potential for negative impact of the Directive on non-commercial European clinical research. Interested researchers within the European Group for Blood and Marrow Transplantation (EBMT) were surveyed to determine whether researcher experiences confirmed this view. Following a pilot study, an internet-based questionnaire was distributed to individuals in key research positions in the European haemopoietic SCT community. Seventy-one usable questionnaires were returned from participants in different EU member states. The results indicate that the perceived impact of the European Clinical Trials Directive has been negative, at least in the research areas of interest to the EBMT.


Assuntos
Transplante de Medula Óssea/normas , Ensaios Clínicos como Assunto , Pesquisa Biomédica/organização & administração , Europa (Continente) , Humanos , Estudos Prospectivos , Inquéritos e Questionários
3.
Appetite ; 51(2): 311-7, 2008 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-18450326

RESUMO

This paper investigates the relationship between general consumer confidence in the safety of food and consumer trust in institutions and organizations. More specifically, using a decompositional regression analysis approach, the extent to which the strength of the relationship between trust and general confidence is dependent upon a particular food chain actor (for example, food manufacturers) is assessed. In addition, the impact of specific subdimensions of trust, such as openness, on consumer confidence are analyzed, as well as interaction effects of actors and subdimensions of trust. The results confirm previous findings, which indicate that a higher level of trust is associated with a higher level of confidence. However, the results from the current study extend on previous findings by disentangling the effects that determine the strength of this relationship into specific components associated with the different actors, the different trust dimensions, and specific combinations of actors and trust dimensions. The results show that trust in food manufacturers influences general confidence more than trust in other food chain actors, and that care is the most important trust dimension. However, the contribution of a particular trust dimension in enhancing general confidence is actor-specific, suggesting that different actors should focus on different trust dimensions when the purpose is to enhance consumer confidence in food safety. Implications for the development of communication strategies that are designed to regain or maintain consumer confidence in the safety of food are discussed.


Assuntos
Comportamento do Consumidor , Qualidade de Produtos para o Consumidor , Alimentos , Confiança , Adulto , Idoso , Participação da Comunidade , Feminino , Alimentos/efeitos adversos , Alimentos/classificação , Contaminação de Alimentos , Humanos , Masculino , Pessoa de Meia-Idade , Opinião Pública , Análise de Regressão , Risco
4.
Risk Anal ; 27(6): 1565-80, 2007 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-18093053

RESUMO

In developing and implementing appropriate food risk management strategies, it is important to understand how consumers evaluate the quality of food risk management practices. The aim of this study is to model the underlying psychological factors influencing consumer evaluations of food risk management quality using structural equation modeling techniques (SEM), and to examine the extent to which the influence of these factors is country-specific (comparing respondents from Denmark, Germany, Greece, Slovenia, and the United Kingdom). A survey was developed to model the factors that drive consumer evaluations of food risk management practices and their relative importance (n= 2,533 total respondents). The measurement scales included in the structural model were configurally and metrically invariant across countries. Results show that some factors appear to drive perceptions of effective food risk management in all the countries studied, such as proactive consumer protection, which was positively related to consumers' evaluation of food risk management quality, while opaque and reactive risk management was negatively related to perceived food risk management quality. Other factors appeared to apply only in certain countries. For example, skepticism in risk assessment and communication practices was negatively related to food risk management quality, particularly so in the UK. Expertise of food risk managers appeared to be a key factor in consumers' evaluation of food risk management quality in some countries. However, trust in the honesty of food risk managers did not have a significant effect on food risk management quality. From the results, policy implications for food risk management are discussed and important directions for future research are identified.


Assuntos
Alimentos , Gestão de Riscos , Animais , Participação da Comunidade , Europa (Continente) , Alimentos/efeitos adversos , Alimentos/normas , Abastecimento de Alimentos/normas , Humanos , Modelos Estatísticos , Análise de Regressão , Gestão de Riscos/normas , Gestão de Riscos/estatística & dados numéricos , Segurança , Confiança
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